Every day, decisions all over the world are made by entities from the largest organizations down to the most solitary individuals, and many, if not most, of those decisions are informed by data. While the growing breadth and widespread availability of data could enhance this decision-making, too frequently this is not the case.
The related fields of visual analytics and information visualization study how the use of interactive visualization can help people understand data better. Based on the same principles as axioms like “Seeing is believing” and “A picture is worth a thousand words,” research in this area examines how visual representations of data — or external cognition aids — help people think.
The data being examined may range from quantitative business information, stored in spreadsheets and databases, to textual documents such as news reports and articles. Often, the data is a heterogeneous collection of items drawn from different sources. But common to all these types of data is our need to draw information out that is hidden — what’s the right course of action? Which option should we choose? What is the best way to accomplish our goal? The answer is buried in there, somewhere, and we just need a way to look for it.
Data visualization is not a new practice — everyone can recognize a line graph or a pie chart. But with modern computer systems that can collect and analyze trillions (or many more) of pieces of data, we need similarly sophisticated tools to deal with it all. Our researchers are developing new, interactive visualization techniques and systems that provide multiple and flexible perspectives on the data being examined. These systems help people and organizations to browse, explore and analyze data that is important to them. Fundamentally, these interactive visualizations are tools for sense-making; they assist us in understanding data by presenting it in a form that can be organized, queried, and explored in order to gain new perspectives and insights about it.